Empirical likelihood for spatial dynamic panel data models

Spatial dynamic panel data (SDPD) models have received great attention in economics in recent 10 years. Existing approaches for the estimation and test of SDPD models are quasi-maximum likelihood (QML) approach and generalized method of moments (GMM). In this article, we introduce the empirical like...

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Bibliographic Details
Published in:Journal of the Korean Statistical Society 2022, 51(2), , pp.500-525
Main Authors: Li, Yinghua, Qin, Yongsong
Format: Article
Language:English
Subjects:
Applied Statistics
Bayesian Inference
Mathematics and Statistics
Research Article
Statistical Theory and Methods
Statistics
Statistics and Computing/Statistics Programs
통계학
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Summary:Spatial dynamic panel data (SDPD) models have received great attention in economics in recent 10 years. Existing approaches for the estimation and test of SDPD models are quasi-maximum likelihood (QML) approach and generalized method of moments (GMM). In this article, we introduce the empirical likelihood (EL) method to the statistical inference for SDPD models. The EL ratio statistics are constructed for the parameters of spatial dynamic panel data models. It is shown that the limiting distributions of the empirical likelihood ratio statistics are chi-squared distributions, which are used to construct confidence regions for the parameters of the models. Simulation results show that the EL based confidence regions outperform the normal approximation based confidence regions.
ISSN:1226-3192
2005-2863
DOI:10.1007/s42952-021-00150-4